Bradley R, Oberg EB, Calabrese C, Standish LJ. Algorithm for Complementary and Alternative Medicine Practice and Research in Type 2 Diabetes.
J Altern Complement Med 2007;
13:159-75. [PMID:
17309390 DOI:
10.1089/acm.2006.6207]
[Citation(s) in RCA: 21] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVE
To develop a model to direct the prescription of nutritional and botanical medicines in the treatment of type 2 diabetes for both clinical and research purposes.
METHODS
Available literature on nutritional and botanical medicines was reviewed and categorized as follows: antioxidant/anti-inflammatory; insulin sensitizer; and beta-cell protectant/insulin secretagogue. Literature describing laboratory assessment for glycemic control, insulin resistance, and beta-cell reserve was also reviewed and a clinical decision tree was developed.
RESULTS
Clinical algorithms were created to guide the use of nutritional and botanic medicines using validated laboratory measures of glycemic control, insulin sensitivity, and beta-cell reserve. Nutrient and botanic medicines with clinical trial research support include coenzyme Q10, carnitine, alpha-lipoic acid, N-acetylcysteine, vitamin D, vitamin C, vitamin E, chromium, vanadium, omega-3 fatty acids, cinnamon (Cinnamomum cassia), fenugreek (Trigonella foenum-graecum), and gymnema (Gymnema sylvestre).
CONCLUSIONS
Clinical algorithms can direct supplementation in clinical practice and provide research models for clinical investigation. Algorithms also provide a framework for integration of future evidence as it becomes available. Research funding to investigate potentially beneficial practices in complementary medicine is critically important for optimal patient care and safety.
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